Learning Method of Recurrent Spiking Neural Networks to Realize Various Firing Patterns and Its Application
Author:
Affiliation:
1. Faculty of Engineering Science, Kansai University
2. Faculty of Information and Human Science, Kyoto Institute of Technology
Publisher
The Society of Instrument and Control Engineers
Link
https://www.jstage.jst.go.jp/article/sicetr/56/10/56_483/_pdf
Reference11 articles.
1. 1) W. Maass and C. Bishop(Eds.): Pulsed Neural Networks, MIT Press (1998)
2. 3) Y. Kuroe and T. Ueyama: Learning Methods of Recurrent Spiking Neural Networks Based on Adjoint Equations Approach, Proc. WCCI 2010 IEEE World Congress on Computational Intelligence, 2561/2568 (2010)
3. 4) S.M. Bohte, J.N. Kok and H.L. Poutre: Error-Backpropagation in Temporally Encoded Networks of Spiking Neurons, Neurocomputing, 48-1-4, 17/37 (2002)
4. 5) J. Kennedy and R.C. Eberhart: Particle swarm optimization, Proc. IEEE International Conference on Neural Networks, 1942/1948 (1995)
5. 7) J.H. Lee, T. Delbruck and M. Pfeiffer: Training Deep Spiking Neural Networks Using Backpropagation, Frontiers in Neuroscience, 10, 508 (2016)
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